The COVID-19 Situation Report is a data intensive report that tries to portray an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic. If you would like to add additional metrics to this report, please send a mail to the author at .

Date of Report

Numbers as on EOD

## [1] "2020-05-24"

COVID-19 Overall Stats (Worldwide)

Overall Confirmed Cases Count Worldwide

## [1] "5407613 (up from 5310362 yesterday: 1.83 % increase)"

Overall Deaths Worldwide

Please note that the deaths is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] "345059 (up from 342097 yesterday: 0.87 % increase)"

Overall Fatality Rate Worldwide in %

Please note that the fatality rate is at the minimum an underestimate as there could be fatalities resulting from the current active cases.

## [1] 6.38



In- Depth Country Wise Stats (With Atleast 1000 COVID-19 Confirmations)

Overall Confirmed Cases and Deaths- Country Wise (With Fatality Rates)

Country_Region TotalConfirmed NewConfirmations CasesPercentIncrease TotalDeaths NewDeaths DeathsPercentIncrease FatalityRate
US 1643246 20634 1.27 97720 633 0.65 5.95
Brazil 363211 15813 4.55 22666 653 2.97 6.24
Russia 344481 8599 2.56 3541 153 4.52 1.03
United Kingdom 260916 2412 0.93 36875 118 0.32 14.13
Spain 235772 482 0.20 28752 74 0.26 12.19
Italy 229858 531 0.23 32785 50 0.15 14.26
France 182709 673 0.37 28370 152 0.54 15.53
Germany 180328 342 0.19 8283 22 0.27 4.59
Turkey 156827 1141 0.73 4340 32 0.74 2.77
India 138536 7113 5.41 4024 156 4.03 2.90
Iran 135701 2180 1.63 7417 58 0.79 5.47
Peru 119959 4205 3.63 3456 83 2.46 2.88
Canada 86106 955 1.12 6534 68 1.05 7.59
China 84095 11 0.01 4638 0 0.00 5.52
Saudi Arabia 72560 2399 3.42 390 11 2.90 0.54
Chile 69102 3709 5.67 718 45 6.69 1.04
Mexico 68620 2764 4.20 7394 215 2.99 10.78
Belgium 57092 282 0.50 9280 43 0.47 16.25
Pakistan 54601 2164 4.13 1133 32 2.91 2.08
Netherlands 45437 172 0.38 5841 11 0.19 12.86
Qatar 43714 1501 3.56 23 2 9.52 0.05
Ecuador 36756 498 1.37 3108 12 0.39 8.46
Belarus 36198 954 2.71 199 5 2.58 0.55
Bangladesh 33610 1532 4.78 480 28 6.19 1.43
Sweden 33459 271 0.82 3998 6 0.15 11.95
Singapore 31616 548 1.76 23 0 0.00 0.07
Switzerland 30736 11 0.04 1906 1 0.05 6.20
Portugal 30623 152 0.50 1316 14 1.08 4.30
United Arab Emirates 29485 781 2.72 245 1 0.41 0.83
Ireland 24639 57 0.23 1608 4 0.25 6.53
South Africa 22583 1240 5.81 429 22 5.41 1.90
Indonesia 22271 526 2.42 1372 21 1.55 6.16
Poland 21326 395 1.89 996 3 0.30 4.67
Kuwait 21302 838 4.09 156 8 5.41 0.73
Colombia 21175 998 4.95 727 22 3.12 3.43
Ukraine 20986 406 1.97 617 12 1.98 2.94
Romania 18070 213 1.19 1185 9 0.77 6.56
Egypt 17265 752 4.55 764 29 3.95 4.43
Israel 16717 5 0.03 279 0 0.00 1.67
Japan 16550 14 0.08 820 12 1.49 4.95
Austria 16503 17 0.10 640 1 0.16 3.88
Dominican Republic 14801 379 2.63 458 0 0.00 3.09
Philippines 14035 258 1.87 868 5 0.58 6.18
Argentina 12076 723 6.37 452 7 1.57 3.74
Denmark 11559 72 0.63 562 1 0.18 4.86
Korea, South 11206 16 0.14 267 1 0.38 2.38
Serbia 11159 67 0.60 238 0 0.00 2.13
Panama 10926 349 3.30 306 7 2.34 2.80
Afghanistan 10582 584 5.84 218 2 0.93 2.06
Bahrain 9138 336 3.82 14 1 7.69 0.15
Czechia 8955 65 0.73 315 1 0.32 3.52
Kazakhstan 8531 612 7.73 35 0 0.00 0.41
Norway 8352 6 0.07 235 0 0.00 2.81
Algeria 8306 193 2.38 600 8 1.35 7.22
Nigeria 7839 313 4.16 226 5 2.26 2.88
Oman 7770 513 7.07 37 1 2.78 0.48
Morocco 7433 27 0.36 199 1 0.51 2.68
Malaysia 7245 60 0.84 115 0 0.00 1.59
Australia 7114 0 0.00 102 0 0.00 1.43
Moldova 7093 99 1.42 250 8 3.31 3.52
Ghana 6683 66 1.00 32 1 3.23 0.48
Armenia 6661 359 5.70 81 4 5.19 1.22
Finland 6579 11 0.17 307 1 0.33 4.67
Bolivia 6263 348 5.88 250 10 4.17 3.99
Cameroon 4890 490 11.14 165 6 3.77 3.37
Iraq 4469 197 4.61 160 8 5.26 3.58
Azerbaijan 4122 140 3.52 49 0 0.00 1.19
Luxembourg 3992 2 0.05 110 1 0.92 2.76
Honduras 3950 473 13.60 180 13 7.78 4.56
Sudan 3820 192 5.29 165 19 13.01 4.32
Hungary 3741 28 0.75 486 4 0.83 12.99
Guatemala 3424 370 12.12 58 3 5.45 1.69
Guinea 3275 99 3.12 20 0 0.00 0.61
Uzbekistan 3164 49 1.57 13 0 0.00 0.41
Senegal 3047 71 2.39 35 1 2.94 1.15
Thailand 3040 0 0.00 56 0 0.00 1.84
Tajikistan 2929 191 6.98 46 2 4.55 1.57
Greece 2878 2 0.07 171 0 0.00 5.94
Bulgaria 2427 19 0.79 130 4 3.17 5.36
Bosnia and Herzegovina 2401 10 0.42 144 3 2.13 6.00
Cote d’Ivoire 2376 10 0.42 30 0 0.00 1.26
Djibouti 2270 0 0.00 10 0 0.00 0.44
Croatia 2244 1 0.04 99 0 0.00 4.41
Congo (Kinshasa) 2141 116 5.73 63 0 0.00 2.94
North Macedonia 1978 37 1.91 113 0 0.00 5.71
Cuba 1941 10 0.52 82 1 1.23 4.22
Gabon 1934 0 0.00 12 0 0.00 0.62
El Salvador 1915 96 5.28 35 2 6.06 1.83
Estonia 1823 2 0.11 64 0 0.00 3.51
Iceland 1804 0 0.00 10 0 0.00 0.55
Lithuania 1623 7 0.43 63 0 0.00 3.88
Somalia 1594 0 0.00 61 0 0.00 3.83
Slovakia 1509 5 0.33 28 0 0.00 1.86
New Zealand 1504 0 0.00 21 0 0.00 1.40
Slovenia 1468 0 0.00 107 1 0.94 7.29
Kyrgyzstan 1403 38 2.78 14 0 0.00 1.00
Maldives 1371 58 4.42 4 0 0.00 0.29
Kenya 1214 22 1.85 51 1 2.00 4.20
Sri Lanka 1141 52 4.78 9 0 0.00 0.79
Venezuela 1121 111 10.99 10 0 0.00 0.89
Guinea-Bissau 1114 0 0.00 6 0 0.00 0.54
Lebanon 1114 17 1.55 26 0 0.00 2.33
Tunisia 1051 3 0.29 48 0 0.00 4.57
Latvia 1047 1 0.10 22 0 0.00 2.10
Kosovo 1032 7 0.68 29 0 0.00 2.81
Mali 1030 15 1.48 65 2 3.17 6.31

In Depth USA Stats (State Wise Figures)

Confirmed Cases and Deaths- States of USA (With Fatality Rates)

State Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
New York 361515 1589 0.44 29141 110 0.38 8.06 18583.49 1497.98 1 in 54
New Jersey 154154 1014 0.66 11138 56 0.51 7.23 17355.40 1253.97 1 in 58
Illinois 110304 2508 2.33 4856 66 1.38 4.40 8704.67 383.21 1 in 115
California 94020 1481 1.60 3754 16 0.43 3.99 2379.52 95.01 1 in 420
Massachusetts 92675 1013 1.11 6372 68 1.08 6.88 13335.49 916.90 1 in 75
Pennsylvania 71563 554 0.78 5136 24 0.47 7.18 5589.99 401.19 1 in 179
Texas 55861 1085 1.98 1528 50 3.38 2.74 1926.52 52.70 1 in 519
Michigan 54679 314 0.58 5228 5 0.10 9.56 5475.10 523.49 1 in 183
Florida 50867 740 1.48 2237 4 0.18 4.40 2368.36 104.15 1 in 422
Maryland 46313 818 1.80 2277 34 1.52 4.92 7660.51 376.63 1 in 131
Georgia 42902 660 1.56 1827 5 0.27 4.26 4040.72 172.08 1 in 247
Connecticut 40468 446 1.11 3693 18 0.49 9.13 11350.56 1035.82 1 in 88
Louisiana 37169 244 0.66 2691 23 0.86 7.24 7995.41 578.86 1 in 125
Virginia 36244 495 1.38 1171 12 1.04 3.23 4246.26 137.19 1 in 236
Ohio 31911 503 1.60 1969 13 0.66 6.17 2729.98 168.45 1 in 366
Indiana 31376 475 1.54 1976 12 0.61 6.30 4660.57 293.51 1 in 215
Colorado 24174 210 0.88 1332 5 0.38 5.51 4197.80 231.30 1 in 238
North Carolina 23365 501 2.19 784 6 0.77 3.36 2227.77 74.75 1 in 449
Minnesota 20573 728 3.67 878 17 1.97 4.27 3647.93 155.68 1 in 274
Tennessee 20111 326 1.65 336 7 2.13 1.67 2943.14 49.17 1 in 340
Washington 19828 563 2.92 1061 11 1.05 5.35 2603.84 139.33 1 in 384
Iowa 17251 353 2.09 456 10 2.24 2.64 5467.71 144.53 1 in 183
Arizona 16377 324 2.02 801 0 0.00 4.89 2150.65 105.19 1 in 465
Wisconsin 15277 400 2.69 510 3 0.59 3.34 2623.82 87.59 1 in 381
Alabama 14478 361 2.56 551 2 0.36 3.81 2952.77 112.38 1 in 339
Rhode Island 14065 113 0.81 608 11 1.84 4.32 13276.87 573.93 1 in 75
Mississippi 13260 255 1.96 625 9 1.46 4.71 4455.42 210.00 1 in 224
Missouri 12149 183 1.53 686 4 0.59 5.65 1979.49 111.77 1 in 505
Nebraska 12134 171 1.43 147 0 0.00 1.21 6272.72 75.99 1 in 159
South Carolina 10096 201 2.03 435 10 2.35 4.31 1960.88 84.49 1 in 510
Kansas 9004 58 0.65 205 0 0.00 2.28 3090.64 70.37 1 in 324
Delaware 8809 280 3.28 326 4 1.24 3.70 9046.34 334.78 1 in 111
Kentucky 8571 0 0.00 391 0 0.00 4.56 1918.45 87.52 1 in 521
Utah 8392 132 1.60 97 0 0.00 1.16 2617.63 30.26 1 in 382
District of Columbia 8110 144 1.81 432 5 1.17 5.33 11491.34 612.12 1 in 87
Nevada 7881 355 4.72 380 -7 -1.81 4.82 2558.64 123.37 1 in 391
New Mexico 6943 318 4.80 317 15 4.97 4.57 3311.19 151.18 1 in 302
Oklahoma 6037 77 1.29 311 0 0.00 5.15 1525.66 78.60 1 in 655
Arkansas 5922 147 2.55 116 1 0.87 1.96 1962.34 38.44 1 in 510
South Dakota 4563 99 2.22 50 0 0.00 1.10 5157.92 56.52 1 in 194
New Hampshire 4149 60 1.47 209 1 0.48 5.04 3051.38 153.71 1 in 328
Oregon 3927 39 1.00 148 1 0.68 3.77 931.07 35.09 1 in 1074
Puerto Rico 3189 89 2.87 127 0 0.00 3.98 998.53 39.77 1 in 1001
Idaho 2626 31 1.19 79 0 0.00 3.01 1465.35 44.08 1 in 682
North Dakota 2418 53 2.24 53 1 1.92 2.19 3172.97 69.55 1 in 315
Maine 2055 42 2.09 78 1 1.30 3.80 1528.78 58.03 1 in 654
West Virginia 1759 54 3.17 72 0 0.00 4.09 984.25 40.29 1 in 1016
Vermont 956 2 0.21 54 0 0.00 5.65 1532.08 86.54 1 in 653
Wyoming 838 25 3.08 12 0 0.00 1.43 1447.93 20.73 1 in 691
Hawaii 643 0 0.00 17 0 0.00 2.64 454.14 12.01 1 in 2202
Montana 479 0 0.00 16 0 0.00 3.34 448.18 14.97 1 in 2231
Alaska 407 0 0.00 10 0 0.00 2.46 556.36 13.67 1 in 1797

US Tested- Confirmed Funnel (All States)

State Level Figures

State Tested Confirmed ConfirmationRate TestsPerMillPopl
New York 1699826 361515 21.27 87378.66
New Jersey 603807 154154 25.53 67979.52
Illinois 747921 110304 14.75 59022.38
California 1582745 94020 5.94 40057.10
Massachusetts 532373 92675 17.41 76605.91
Pennsylvania 396095 71563 18.07 30940.11
Texas 763766 55861 7.31 26340.50
Michigan 451232 54679 12.12 45182.58
Florida 871235 50867 5.84 40564.56
Maryland 240362 46313 19.27 39757.65
Georgia 481954 42902 8.90 45392.75
Connecticut 214136 40468 18.90 60061.36
Louisiana 316036 37169 11.76 67982.36
Virginia 244085 36244 14.85 28596.39
Ohio 324553 31911 9.83 27765.44
Indiana 220801 31376 14.21 32797.66
Colorado 150051 24174 16.11 26056.24
North Carolina 336656 23365 6.94 32098.90
Minnesota 197964 20573 10.39 35102.29
Tennessee 383576 20111 5.24 56134.38
Washington 316276 19828 6.27 41533.87
Iowa 127756 17251 13.50 40492.29
Arizona 183641 16377 8.92 24116.03
Wisconsin 201483 15277 7.58 34604.60
Alabama 185799 14478 7.79 37893.53
Rhode Island 132701 14065 10.60 125265.14
Mississippi 137902 13260 9.62 46335.72
Missouri 151619 12149 8.01 24704.00
Nebraska 83205 12134 14.58 43013.16
South Carolina 163947 10096 6.16 31842.32
Kansas 76434 9004 11.78 26236.10
Delaware 51870 8809 16.98 53267.53
Kentucky 169856 8571 5.05 38018.90
Utah 194433 8392 4.32 60647.39
District of Columbia 51991 8110 15.60 73667.83
Nevada 110281 7881 7.15 35803.71
New Mexico 169119 6943 4.11 80654.65
Oklahoma 160980 6037 3.75 40682.63
Arkansas 108581 5922 5.45 35979.89
South Dakota 34905 4563 13.07 39455.88
New Hampshire 59539 4149 6.97 43787.98
Oregon 112195 3927 3.50 26600.76
Puerto Rico 3189 3189 100.00 998.53
Idaho 41406 2626 6.34 23105.19
North Dakota 65488 2418 3.69 85935.27
Maine 37505 2055 5.48 27901.10
West Virginia 85694 1759 2.05 47950.17
Vermont 28590 956 3.34 45818.12
Wyoming 20034 838 4.18 34615.44
Hawaii 49572 643 1.30 35011.64
Montana 33381 479 1.43 31232.87
Alaska 43507 407 0.94 59472.76

In Depth India Stats (State Wise Figures)

Confirmed Cases and Deaths (States of India)

State Confirmed NewConfirmations CasesPercentIncrease Recovered RecoveryRate Active Deaths NewDeaths DeathsPercentIncrease FatalityRate
Maharashtra 50231 3041 6.44 14600 29.07 33996 1635 58 3.68 3.25
Tamil Nadu 16277 765 4.93 8324 51.14 7841 112 8 7.69 0.69
Gujarat 14063 394 2.88 6412 45.59 6793 858 29 3.50 6.10
Delhi 13418 508 3.93 6540 48.74 6617 261 30 12.99 1.95
Rajasthan 7028 286 4.24 3848 54.75 3017 163 3 1.88 2.32
Madhya Pradesh 6665 294 4.61 3408 51.13 2967 290 9 3.20 4.35
Uttar Pradesh 6268 251 4.17 3538 56.45 2569 161 6 3.87 2.57
West Bengal 3667 208 6.01 1339 36.51 2056 272 3 1.12 7.42
Andhra Pradesh 2780 66 2.43 1841 66.22 883 56 0 0.00 2.01
State Unassigned 2642 743 39.13 0 0.00 2642 0 0 NaN 0.00
Bihar 2574 180 7.52 702 27.27 1861 11 0 0.00 0.43
Karnataka 2089 130 6.64 654 31.31 1391 42 0 0.00 2.01
Punjab 2060 15 0.73 1898 92.14 122 40 1 2.56 1.94
Telangana 1854 41 2.26 1092 58.90 709 53 4 8.16 2.86
Jammu and Kashmir 1621 52 3.31 809 49.91 791 21 0 0.00 1.30
Odisha 1336 67 5.28 550 41.17 779 7 0 0.00 0.52
Haryana 1184 53 4.69 765 64.61 403 16 0 0.00 1.35
Kerala 848 53 6.67 520 61.32 322 6 1 20.00 0.71
Assam 393 46 13.26 58 14.76 328 4 0 0.00 1.02
Jharkhand 370 20 5.71 148 40.00 218 4 1 33.33 1.08
Uttarakhand 317 73 29.92 58 18.30 255 3 2 200.00 0.95
Chandigarh 262 37 16.44 179 68.32 79 4 1 33.33 1.53
Chhattisgarh 252 38 17.76 64 25.40 188 0 0 NaN 0.00
Himachal Pradesh 203 18 9.73 59 29.06 137 4 0 0.00 1.97
Tripura 194 3 1.57 165 85.05 29 0 0 NaN 0.00
Goa 66 11 20.00 16 24.24 50 0 0 NaN 0.00
Ladakh 52 3 6.12 43 82.69 9 0 0 NaN 0.00
Puducherry 41 15 57.69 12 29.27 29 0 0 NaN 0.00
Andaman and Nicobar Islands 33 0 0.00 33 100.00 0 0 0 NaN 0.00
Manipur 32 5 18.52 2 6.25 30 0 0 NaN 0.00
Meghalaya 14 0 0.00 12 85.71 1 1 0 0.00 7.14
Arunachal Pradesh 2 1 100.00 1 50.00 1 0 0 NaN 0.00
Dadra and Nagar Haveli and Daman and Diu 2 0 0.00 1 50.00 1 0 0 NaN 0.00
Mizoram 1 0 0.00 1 100.00 0 0 0 NaN 0.00
Sikkim 1 0 0.00 0 0.00 1 0 0 NaN 0.00
Lakshadweep 0 0 NaN 0 NaN 0 0 0 NaN NaN
Nagaland 0 0 NaN 0 NaN 0 0 0 NaN NaN

In Depth Italy Stats (Region Wise Figures)

Confirmed Cases and Deaths- Regions of Italy (With Fatality and Confirmation Rates)

Region Swabs Confirmations NewConfirmations CasesPercentIncrease ConfirmationRate HospitalizedWithSymptoms IntensiveCare ActiveCases Deceased FatalityRate
Lombardia 670241 87110 285 0.33 13.00 4017 197 25614 15840 18.18
Piemonte 285160 30180 43 0.14 10.58 1283 75 7703 3783 12.53
Emilia-Romagna 291876 27558 45 0.16 9.44 519 83 4457 4055 14.71
Veneto 582709 19086 17 0.09 3.28 185 11 2660 1869 9.79
Toscana 229135 10062 15 0.15 4.39 148 38 1700 1013 10.07
Liguria 93173 9480 53 0.56 10.17 247 18 1624 1419 14.97
Lazio 233498 7627 20 0.26 3.27 1088 61 3569 684 8.97
Marche 95715 6714 13 0.19 7.01 101 13 1692 994 14.80
Campania 172106 4749 5 0.11 2.76 311 8 1268 405 8.53
Puglia 103570 4458 10 0.22 4.30 204 17 1793 487 10.92
P.A. Trento 79788 4404 9 0.20 5.52 27 4 535 457 10.38
Sicilia 133249 3423 2 0.06 2.57 91 9 1453 269 7.86
Friuli Venezia Giulia 118852 3236 3 0.09 2.72 62 1 412 329 10.17
Abruzzo 66486 3226 5 0.16 4.85 149 3 1092 398 12.34
P.A. Bolzano 60573 2593 3 0.12 4.28 30 5 195 291 11.22
Umbria 63717 1430 0 0.00 2.24 15 2 53 75 5.24
Sardegna 50796 1356 0 0.00 2.67 51 3 245 129 9.51
Valle d’Aosta 14079 1178 1 0.08 8.37 23 1 32 143 12.14
Calabria 62952 1157 0 0.00 1.84 43 1 275 96 8.30
Molise 13226 432 1 0.23 3.27 6 2 183 22 5.09
Basilicata 26111 399 1 0.25 1.53 13 1 39 27 6.77

In Depth Canada Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of Canada (With Fatality Rates)

Province Confirmed NewConfirmations CasesPercentIncrease Deaths NewDeaths DeathsPercentIncrease FatalityRate ConfirmedCasesPerMillPopl DeathsPerMillPopl InfectionOdds
Quebec 47420 573 1.22 3985 44 1.12 8.40 5554.21 466.75 1 in 180
Ontario 26897 337 1.27 2181 24 1.11 8.11 1828.26 148.25 1 in 547
Alberta 6860 42 0.62 135 0 0.00 1.97 1554.45 30.59 1 in 643
British Columbia 2517 0 0.00 157 0 0.00 6.24 492.48 30.72 1 in 2031
Nova Scotia 1050 1 0.10 58 0 0.00 5.52 1074.22 59.34 1 in 931
Saskatchewan 632 2 0.32 7 0 0.00 1.11 534.84 5.92 1 in 1870
Manitoba 292 0 0.00 7 0 0.00 2.40 211.98 5.08 1 in 4718
Newfoundland and Labrador 260 0 0.00 3 0 0.00 1.15 498.69 5.75 1 in 2005
New Brunswick 121 0 0.00 0 0 NaN 0.00 155.13 0.00 1 in 6446
Prince Edward Island 27 0 0.00 0 0 NaN 0.00 170.72 0.00 1 in 5858
Yukon 11 0 0.00 0 0 NaN 0.00 267.78 0.00 1 in 3734
Northwest Territories 5 0 0.00 0 0 NaN 0.00 111.35 0.00 1 in 8981

In Depth China Stats (With Province Level Figures)

Confirmed Cases and Deaths- Provinces of China (With Fatality Rates)

Province Confirmed Deaths FatalityRate
Hubei 68135 4512 6.62
Guangdong 1592 8 0.50
Henan 1276 22 1.72
Zhejiang 1268 1 0.08
Hong Kong 1065 4 0.38
Hunan 1019 4 0.39
Anhui 991 6 0.61
Heilongjiang 945 13 1.38
Jiangxi 937 1 0.11
Shandong 788 7 0.89
Shanghai 668 7 1.05
Jiangsu 653 0 0.00
Beijing 593 9 1.52
Chongqing 579 6 1.04
Sichuan 564 3 0.53
Fujian 356 1 0.28
Hebei 328 6 1.83
Shaanxi 308 3 0.97
Guangxi 254 2 0.79
Inner Mongolia 227 1 0.44
Shanxi 198 0 0.00
Tianjin 192 3 1.56
Yunnan 185 2 1.08
Hainan 169 6 3.55
Jilin 155 2 1.29
Liaoning 149 2 1.34
Guizhou 147 2 1.36
Gansu 139 2 1.44
Xinjiang 76 3 3.95
Ningxia 75 0 0.00
Macau 45 0 0.00
Qinghai 18 0 0.00
Tibet 1 0 0.00

Time Series Curves (Top 20 Countries with the Highest Cases)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most confirmed COVID-19 cases as of today in decreasing order of confirmations.

Confirmed Cases Count (Linear)

Country Wise Time Series Curve

Confirmed Cases Count (Logarithmic)

Country Wise Time Series Curve

Time Series Curves (Top 20 Countries with the Highest Deaths)

The time series curves (both linear and logarithmic) are printed for the top 20 countries with the most COVID-19 deaths as of today in decreasing order of confirmations.

Death Count (Linear)

Country Wise Time Series Curve

Death Count (Logarithmic)

Country Wise Time Series Curve

Epidemic Curve: Delta in the past 24 hrs (Top 20 Countries with the Highest Cases)

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various countries. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 countries in the world as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Delta in Confirmed Cases

Number of New Cases in the past 24 hrs

Delta in Deaths

Number of Deaths in the past 24 hrs

Measuring Outbreak Velocity: 5 Day Lagging Average Doubling Time (Top 20 Countries with the Highest Cases)

The velocity of an outbreak is determined by a construct known as doubling time. This value describes the number of days, on average, required for the number of cases to double in a given area. For our analysis we use average doubling time, which can be defined as the number of days, on average, required for the average number of COVID-19 cases to double in a given area.

This measure can describe COVID-19 behavior worldwide, in a country, or even in a smaller region such as a state. For our analysis, we will discuss average doubling time at a national level for the top 20 most affected countries.

Below, we have calculated average doubling time for several nations, on a trailing, rolling 5-day basisbased on today’s case values. A decline in average doubling time indicates that the COVID-19 outbreak (confirmation rate) is accelerating (average cases double in fewer days), while an increase of average doubling time indicates that the outbreak is slowing.

Ideally, when social distancing and lockdowns are implemented aggressively in a country and after some period of delay, doubling times should begin to increase in a matter of days, weeks, or months, depending upon the severity of the epidemic and the degree of social distancing achievable.

Given the fact that many countries across the world have already enacted or implemented social distancing measures, this is why one should be cautious not to extrapolate COVID-19 growth rates from trailing statistics.

5 Day Lagging Avg Doubling Time of Confirmations

Confirmed Cases and Deaths Per Million Population and Infection Odds

This metric confirmed cases per million population and deaths per million population shows the extent to which the disease has spread with respect to the population of the country. The metric Infection Odds shows 1 in how many people are infected with COVID-19 in the corresponding country.

For the top 20 countries with most confirmed cases excluding cruise ships

Country_Region ConfirmedCasesPerMillionPopl DeathsPerMillionPopl InfectionOdds
US 5022.15 298.66 1 in 199
Brazil 1735.36 108.29 1 in 576
Russia 2383.95 24.51 1 in 419
United Kingdom 3927.09 555.01 1 in 255
Spain 5052.98 616.20 1 in 198
Italy 3800.56 542.08 1 in 263
France 2727.41 423.50 1 in 367
Germany 2178.14 100.05 1 in 459
Turkey 1940.69 53.71 1 in 515
India 103.46 3.01 1 in 9665
Iran 1672.02 91.39 1 in 598
Peru 3728.91 107.43 1 in 268
Canada 2290.66 173.82 1 in 437
China 60.67 3.35 1 in 16481
Saudi Arabia 2202.79 11.84 1 in 454
Chile 3828.37 39.78 1 in 261
Mexico 531.11 57.23 1 in 1883
Belgium 5008.07 814.04 1 in 200
Pakistan 277.16 5.75 1 in 3608
Netherlands 2644.76 339.99 1 in 378

US Detailed State and County Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the state/ county level in USA.

Epidemic Curve: Delta in Confirmed Cases in US States

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in various US states. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The below charts show if this has happened for the worst affected 20 states in USA as of today. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in US States

Number of Deaths in the past 24 hrs

Top 50 US Counties with the Highest Cases and Deaths

All NYC boroughs are mentioned together as New York County

County State Confirmations Deaths FatalityRate
New York New York 198123 21216 10.71
Cook Illinois 72010 3304 4.59
Los Angeles California 45017 2106 4.68
Nassau New York 39837 2094 5.26
Suffolk New York 38964 1834 4.71
Westchester New York 32968 1337 4.06
Philadelphia Pennsylvania 21234 1233 5.81
Middlesex Massachusetts 20437 1518 7.43
Wayne Michigan 19771 2359 11.93
Hudson New Jersey 18879 1139 6.03
Bergen New Jersey 17804 1525 8.57
Suffolk Massachusetts 17417 838 4.81
Essex New Jersey 17214 1600 9.29
Miami-Dade Florida 16845 631 3.75
Passaic New Jersey 15686 890 5.67
Middlesex New Jersey 15351 955 6.22
Union New Jersey 15169 1025 6.76
Fairfield Connecticut 15114 1215 8.04
Prince George’s Maryland 13521 490 3.62
Essex Massachusetts 13457 859 6.38
Rockland New York 12963 618 4.77
Harris Texas 10921 220 2.01
New Haven Connecticut 10905 903 8.28
Providence Rhode Island 10607 0 0.00
Worcester Massachusetts 10431 679 6.51
Orange New York 10225 429 4.20
Montgomery Maryland 9922 558 5.62
Hartford Connecticut 9686 1175 12.13
Marion Indiana 9132 533 5.84
Fairfax Virginia 8989 327 3.64
Dallas Texas 8827 211 2.39
Ocean New Jersey 8372 686 8.19
Maricopa Arizona 8277 384 4.64
Oakland Michigan 8215 955 11.63
District of Columbia District of Columbia 8110 432 5.33
Norfolk Massachusetts 7812 782 10.01
Monmouth New Jersey 7800 556 7.13
King Washington 7783 547 7.03
Lake Illinois 7615 250 3.28
Plymouth Massachusetts 7559 508 6.72
Jefferson Louisiana 7248 433 5.97
DuPage Illinois 7060 340 4.82
Orleans Louisiana 6953 500 7.19
Hennepin Minnesota 6918 534 7.72
Broward Florida 6697 292 4.36
Bristol Massachusetts 6596 369 5.59
San Diego California 6559 249 3.80
Montgomery Pennsylvania 6525 633 9.70
Macomb Michigan 6499 778 11.97
Riverside California 6464 290 4.49

Overall US Choropleth Map

Choropleths are an ideal way to visualize the past/ current COVID-19 hotspots within a country. The below are the hotspots in the US.

County level COVID-19 Confirmations Map

Canada Detailed Province Level Curves

This section of the report might be of interest to people who want an an accurate data oriented picture of the 2019- 2020 COVID-19 pandemic at the province level in Canada.

The COVID-19 epidemic curve, also known as an COVID-19 epi curve or COVID-19 epidemiological curve, is a statistical chart to visualise the onset and progression of the COVID-19 outbreak in the most affected Canadian provinces- Quebec, Ontario, Alberta and British Columbia. The term flattening of the epidermic curve is referred to as the drastic reduction of new cases which can be seen in the dip in the number of new cases in the past 24 hrs. The fitted line in the below bars show the last 7 day average of new cases/ new deaths.

Epidemic Curve: Delta in Confirmed Cases in Canadian Provinces

Number of New Cases in the past 24 hrs

Epidermic Curve: Delta in Deaths in Canadian Provinces

Number of Deaths in the past 24 hrs

Data Sources

CSSEGISandData, The NY Times, amodm/api-covid19-in and pcm-dpc